1. Field of the Invention
The present invention relates to image recognition and tracking performed in application fields using images, such as, automation systems, intelligent vehicle systems, and the like, and more particularly, to a landmark used to effectively determine the location of an autonomous vehicle such as a mobile robot, and a self-localization apparatus and method using the landmark.
2. Description of the Related Art
With an increase in the interest in mobile robots, various types of such robots have been actively developed. Mobile robots are applied to various fields, and must have four functions associated with their movements in order to navigate autonomous vehicles.
The first function is a map building function, the second one is a self-localization or self-positioning function, the third one is an obstacle avoidance function, and the fourth one is a path planning function.
The map building function, by which a map about a given space, that is, a working environment, is built, can be considered essential to plan a work to be allocated to an autonomous vehicle. The self-localization or self-positioning function denotes a function to self-ascertain the present location in order to accomplish a given command, for example, a command “move from the current location to a new space.” The obstacle avoidance function denotes sensing and avoiding an unexpected obstacle that occurs during execution of a scheduled work. The path planning function denotes planning a progress of a robot from its initial state to a final target state.
In particular, an autonomous vehicle can be more easily navigated by providing it with accurate information on its location and orientation. The information can be provided to autonomous vehicles by a dead reckoning method using distances and directions, an inertial navigation using an accelerometer and a gyrosenser, and a satellite-based positioning method. However, these methods have drawbacks. For example, the dead reckoning method has a low accuracy due to an accumulation of errors caused by slipping of autonomous vehicles. The inertial navigation has a low accuracy due to an accumulation of errors caused by integration. The satellite-based positioning method requires a secure communications path with a satellite and cannot provide accurate location information necessary for orbit correction.
Besides, a self-positioning method can be used, in which location and orientation information can be provided to autonomous vehicles using landmarks disposed at pre-known locations within a work environment.
The landmarks are read and processed by a vision system, which is carried by an autonomous vehicle. If a landmark is detected and recognized by the vision system, the unique location of the detected landmark is determined, and the location of the autonomous vehicle is determined in accordance with the location of the landmark.
However, current methods using landmarks have some problems. If a working environment is messy or unevenly bright, or if parts of landmarks are occluded, errors occur when the landmarks are detected and recognized. Consequently, errors exist in a determined location of an autonomous vehicle. Also, the current methods using landmarks make it difficult to ascertain information on a location based on the X and Y axes of an image plane and information on an angle made by a camera with each of the landmarks from an acquired landmark image.